In this book, we have proposed a novel noise removal method of PCG signals using robust feature space optimization. The proposed method identifies the noisy PCG signals and eliminates them to ensure effective clinical analytics. We depict more than 85% accuracy and high specificity of identifying noisy PCG signals while experimenting over annotated PCG datasets from large publicly available MIT-Physionet database. We have also shown that propose noise removal has the capability to significantly improve the clinical utility like detection of cardiac normal/ abnormal condition from heart sound or PCG signals.
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Arijit Ukil has more than 15 years of research experience, worked as Scientist in DRDO, India. Currently he is Scientist in Tata Consultancy Services, India. He has published more than 50 research papers, 4 book chapters, 40 patents with 15 grants. He holds Masters in Engineering from Jadavpur University, India. He is a Senior Member, IEEE.
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In this book, we have proposed a novel noise removal method of PCG signals using robust feature space optimization. The proposed method identifies the noisy PCG signals and eliminates them to ensure effective clinical analytics. We depict more than 85% accuracy and high specificity of identifying noisy PCG signals while experimenting over annotated PCG datasets from large publicly available MIT-Physionet database. We have also shown that propose noise removal has the capability to significantly improve the clinical utility like detection of cardiac normal/ abnormal condition from heart sound or PCG signals. 88 pp. Englisch. Bestandsnummer des Verkäufers 9786138388869
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Ukil ArijitArijit Ukil has more than 15 years of research experience, worked as Scientist in DRDO, India. Currently he is Scientist in Tata Consultancy Services, India. He has published more than 50 research papers, 4 book chapters, . Bestandsnummer des Verkäufers 385848287
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -In this book, we have proposed a novel noise removal method of PCG signals using robust feature space optimization. The proposed method identifies the noisy PCG signals and eliminates them to ensure effective clinical analytics. We depict more than 85% accuracy and high specificity of identifying noisy PCG signals while experimenting over annotated PCG datasets from large publicly available MIT-Physionet database. We have also shown that propose noise removal has the capability to significantly improve the clinical utility like detection of cardiac normal/ abnormal condition from heart sound or PCG signals.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 88 pp. Englisch. Bestandsnummer des Verkäufers 9786138388869
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In this book, we have proposed a novel noise removal method of PCG signals using robust feature space optimization. The proposed method identifies the noisy PCG signals and eliminates them to ensure effective clinical analytics. We depict more than 85% accuracy and high specificity of identifying noisy PCG signals while experimenting over annotated PCG datasets from large publicly available MIT-Physionet database. We have also shown that propose noise removal has the capability to significantly improve the clinical utility like detection of cardiac normal/ abnormal condition from heart sound or PCG signals. Bestandsnummer des Verkäufers 9786138388869
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Taschenbuch. Zustand: Neu. Robust Feature Space Optimization and Noise Removal from PCG | Arijit Ukil (u. a.) | Taschenbuch | 88 S. | Englisch | 2018 | LAP LAMBERT Academic Publishing | EAN 9786138388869 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu Print on Demand. Bestandsnummer des Verkäufers 113474534
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